ITI and the Multimedia Knowledge and Social Media Analytics Lab have been accepted as associate member of the Big Data Value Association (http://www.bigdatavalue.eu/). The aim of the BDVA is to provide a platform for stakeholders from the Big Data Value community in Europe to easily access information, exchange ideas and respond to activities concerning a Big Data Value initiative that is currently taking form at EU level. As a member, ITI and MKLab will contribute to the different task forces and activities of the association.

MKLab participates in two new Horizon 2020 projects: STEP and KRISTINA, which are starting in spring 2015. STEP deals with developing a cloud eParticipation SaaS platform, enhanced with web/social media mining, gamification, machine translation, and visualisation features, which will promote the societal and political participation of young people in the decision-making process on environmental issues. KRISTINA aims at developing a human-like socially competent agent that serves for migrants with language and cultural barriers in the host country as a trusted information provision party and mediator in questions related to basic care and healthcare.

MKLab participated again this year in the annual TRECVID benchmarking activity, organized by the US National Institute for Standards and Technology (NIST). MKLab participated in four TRECVID tasks: Semantic Indexing (SIN), Event Detection in Internet Multimedia (MED), Multimedia Event Recounting (MER), and Instance Search (INS). Our results in these tasks were very good, significantly improving the results we had obtained in previous years.

The paper "Brain source localization of MMN, P300 and N400: aging and gender differences" by A. Tsolaki, V. Kosmidou, L. Hadjileontiadis, I. Kompatsiaris and M. Tsolaki, has been accepted for publication in the Brain Research Journal, Elsevier (IF=2,828). This work has been supported by the ARISTEIA project CBP: Cognitive Brain signal Processing lab.

The paper on “Multi-entity bayesian networks for knowledge-driven analysis of ICH content” by Giannis Chantas, Alexandros Kitsikidis, Spiros Nikolopoulos, Kosmas Dimitropoulos, Stella Douka, Ioannis Kompatsiaris and Nikos Grammalidis received the Best Student Paper Award at the ECCV Workshop on Computer vision + ONTology Applied Cross-disciplinary Technologies, which was held in Zurich, Switzerland, in September 2014.